Is Data Science a Dying Career? Posted on : Jan 24 - 2022

Introduction

 I recently read an article describing data science as an oversaturated field. The article predicted that ML engineers would replace data scientists in the upcoming years.

According to the author of this article, most companies worked to solve very similar business problems with data science. Due to this, it wouldn’t be necessary for data scientists to come up with novel methods of solving problems.

The author went on to say that only basic data science skills were required in order to solve problems in most data-driven organizations. This role could easily be replaced by a machine learning engineer — a person with basic knowledge of data science algorithms, who also possessed knowledge of deploying ML models.

I have read many similar articles in the past year.

Some of them state that the role of a data scientist will be replaced by tools like AutoML, while others refer to data science as a “dying field” that will soon be surpassed by roles like data engineering and ML operations.

As someone who works closely with different pillars of the data industry, I would like to provide my opinion on this topic, and answer questions along these lines:

• Is data science a dying career, and will there still be demand for it in the next few years?
• Will automated tools render data scientists jobless?
• Is data science oversaturated, and will the field be replaced by newer roles in the near future?
• Are data scientists profitable to organizations? How do they add value to businesses?

Are Data Scientists Needed?

The data science workflow within most organizations is pretty similar. Many companies hire data scientists to solve similar business problems. Most of the models built don’t require you to come up with novel solutions. View More